Daniel Russo
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Philip H. Geier Jr. Associate Professor at Columbia Business School |
About Me
I joined the Decision, Risk, and Operations division of the Columbia Business School in Summer 2017. I teach a core MBA course on statistics and a PhD course on dynamic optimization. My research lies at the intersection of statistical machine learning and online decision making, mostly falling under the broad umbrella of reinforcement learning. Outside academia, I work with Spotify to apply reinforcement learning style models to audio recommendations.
My research has been recognized by the Frederick W. Lanchester Prize, a Junior Faculty Interest Group Best Paper Award, and first place in the George Nicholson Student Paper Competition. I currently serve as an associate editor at Management Science and Stochastic Systems.
Prior to joining Columbia, I spent one great year as an assistant professor in the MEDS department at Northwestern's Kellogg School of Management and one year at Microsoft Research in New England as Postdoctoral Researcher. I received my PhD from Stanford University in 2015, where I was advised by Benjamin Van Roy. In 2011 I received my BS in Mathematics and Economics from the University of Michigan.